Question

使用此数据：

https://www.health.govt.nz/system/files/documents/publications/suicide-2015-tables.xlsx

第一列包含行： “自杀人数男
女
总计
年龄标准化率（每10万例死亡人数）
男
女
总计”

但是，我需要将它们用作列标题。是通过pivot_longer（）完成的吗？

谢谢

Answer 1

这是一个非常丑陋的数据文件，但希望它可以达到您想要的：

library(dplyr)
library(tidyr)

# After downloading the file in your project folder
dat <- readxl::read_excel("suicide-2015-tables.xlsx", skip = 2)

dat %>% 
  select(variables = ...1, `2006`:`2015`) %>% # Remove unneeded/blank columns
  mutate(headers = if_else(is.na(`2006`), variables, NA_character_)) %>% # Create a headers variable
  fill(headers, .direction = "down") %>% # Fill the headers down
  pivot_longer(`2006`:`2015`, names_to = "year", values_to = "counts") %>% # Reshape data from wide to long
  drop_na() %>% 
  unite("headers_vars", headers, variables, sep = " - ") %>% # Create a new variable that combines the headers and the subgroup breakdown
  pivot_wider(names_from = headers_vars, values_from = counts) # Reshape back from long to wide

# A tibble: 10 x 15
   year  `Number of suic~ `Number of suic~ `Number of suic~ `Age-standardis~ `Age-standardis~ `Age-standardis~ `Age-specific r~
   <chr>            <dbl>            <dbl>            <dbl>            <dbl>            <dbl>            <dbl>            <dbl>
 1 2006               388              138              526             18.6             6.25             12.2             19.7
 2 2007               371              116              487             17.4             5.01             11.0             15.2
 3 2008               381              139              520             17.6             6.24             11.8             19.5
 4 2009               393              117              510             17.9             5.03             11.3             18.1
 5 2010               386              149              535             17.3             6.63             11.8             17.7
 6 2011               377              116              493             17.0             5.06             10.9             20.1
 7 2012               404              146              550             18.1             6.39             12.1             23.0
 8 2013               367              147              514             16.0             6.41             11.0             17.8
 9 2014               380              130              510             16.5             5.4              10.8             14.1
10 2015               384              143              527             16.4             6.1              11.1             16.9
# ... with 7 more variables: `Age-specific rates by life-stage age group (deaths per 100,000) - 25–44` <dbl>, `Age-specific rates by
#   life-stage age group (deaths per 100,000) - 45–64` <dbl>, `Age-specific rates by life-stage age group (deaths per 100,000) - 65+` <dbl>,
#   `Age-standardised suicide rates for Māori (deaths per 100,000) - Male` <dbl>, `Age-standardised suicide rates for Māori (deaths per
#   100,000) - Female` <dbl>, `Age-standardised suicide rates for non-Māori (deaths per 100,000) - Male` <dbl>, `Age-standardised suicide
#   rates for non-Māori (deaths per 100,000) - Female` <dbl>

ivot_longer，将第一列的行名转换为列名

1 个答案: